Banking Southeast Asia

Regional Bank: AgentOps for Customer Service AI

A top-5 regional bank needed governance, compliance evidence, and cost visibility for their production AI agents. Rotascale delivered operational control at scale.

Challenge

Production AI without production governance

The bank had deployed AI-powered customer service agents across mobile app, web chat, and call center channels. The POC was successful — agents handled 60% of inquiries without human intervention.

But as they scaled to production, problems emerged:

Reliability issues

  • Agents occasionally provided incorrect product information
  • Compliance disclosures were inconsistently delivered
  • No way to detect when agents were "confidently wrong"

Operational blindness

  • No unified view of agent performance across channels
  • Couldn't trace why a specific agent made a specific decision
  • When issues arose, debugging took days

Regulatory pressure

  • Central bank required explainability for AI-assisted decisions
  • Audit team couldn't produce evidence of AI governance
  • Risk committee flagged customer-facing AI as uncontrolled

Cost concerns

  • LLM costs scaling linearly with volume
  • No visibility into cost per interaction by use case
  • Finance questioning ROI as costs grew
Approach

16-week implementation program

Phase 1 Weeks 1-3

Assessment

  • Inventoried all deployed agents across channels
  • Mapped current monitoring and governance gaps
  • Assessed regulatory requirements (MAS guidelines)
  • Identified quick wins and critical risks
Phase 2 Weeks 4-6

Architecture Design

  • Designed AgentOps architecture for the bank's environment
  • Defined agent identity schema integrated with existing IAM
  • Created policy framework aligned with compliance requirements
  • Specified observability requirements for audit
Phase 3 Weeks 7-14

Implementation

  • Deployed AgentOps Platform in bank's private cloud
  • Implemented Guardian for reliability monitoring
  • Integrated reasoning capture ("Flight Recorder")
  • Built compliance dashboards for risk team
Phase 4 Weeks 15-16

Enablement

  • Trained platform team on AgentOps operations
  • Trained compliance team on audit reporting
  • Established runbooks for incident response
  • Defined ongoing governance processes
Solution

Enterprise agent operations infrastructure

AgentOps Platform deployment

  • Centralized registry for 12 distinct agent types
  • Unified identity with bank's IAM (agent URNs)
  • Policy engine enforcing 47 compliance rules
  • Full reasoning capture for every interaction

Guardian integration

  • Real-time monitoring for hallucination indicators
  • Drift detection comparing weekly behavioral baselines
  • Confidence calibration tracking
  • Automated alerting to ops team

Compliance infrastructure

  • Audit trail for every agent decision
  • On-demand explainability reports
  • MAS-aligned governance documentation
  • Quarterly compliance reporting automation

Cost attribution

  • Token-level cost tracking by agent, channel, use case
  • Real-time cost dashboards
  • Budget alerts by business unit
  • ROI reporting by interaction type
Results

Measurable transformation

Metric Before After Change
Agent reliability (human-verified) 87% 96% +9%
Mean time to debug issues 3.2 days 4 hours -95%
Compliance audit preparation 6 weeks 2 days -97%
Cost visibility None Real-time Complete
Regulatory findings 3 critical 0 -100%

Additional outcomes

  • Passed MAS technology risk inspection with commendation
  • Expanded agent deployment to 3 additional use cases
  • Reduced compliance team effort by 60%
  • Board approved next phase of AI investment

"We knew our AI agents worked. What we didn't know was whether they were working correctly, consistently, and compliantly. Rotascale gave us the visibility and governance we needed to scale with confidence. The regulator was impressed — and that doesn't happen often."

— Chief Technology Officer
Your turn

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